1. Field of the Invention
The present invention relates to an apparatus and a method for noise removal, and more particularly to an apparatus and a method for removing noise that occurs during a call.
2. Description of the Related Art
When a user makes a call using a mobile communication terminal, various noise signals according to a neighboring environment can be input through a microphone within a terminal. One of the most important factors affecting a sound quality is environmental noise. Accordingly, a noise suppressing method provides a potential differentiation factor to manufacturers of a mobile communication terminal.
In large, noise as described above includes stationary noise and non-stationary noise. The stationary noise refers to consistent and relatively time-invariant noise such as car noise or wind noise, and the non-stationary noise refers to time-varying noise where the voice of people or various types of noise are mixed together, especially in a restaurant, a department store, etc. Since the occurrence of noise degrades a sound quality, various noise removal methods can be used to remove such noise of the other party during a call.
As one of the noise removal methods, there is a method using one microphone. This method assumes an initial signal with a period of several milliseconds as the noise. This method removes noise in a noise area and a voice area by obtaining Signal-to-Noise Ratio (SNR) based on the signal, and updates the initial noise signal in the noise area and subtracts the noise in the voice area without any update. With such a one microphone-using noise removal method, it is not easy to distinguish between noise and voice, and in the case of the non-stationary noise, the noise in the voice section also varies. Therefore, a significant distortion of the voice signal takes place when the noise is removed by using previous noise data. To overcome these technological limitations, noise removal algorithms by mounting two or more microphones and using a signal processing have been proposed.
Referring to FIG. 1, an example of such a two microphone-using method will be described. FIG. 1 is an exemplary diagram of a mobile communication terminal having two microphones mounted, wherein a microphone 10 is mounted on the front side of the mobile communication terminal, the microphone 10 receiving the voice of a speaking person, and a microphone 20 is mounted on the back side thereof, the microphone 20 receiving noise. Through the microphone 10 of the front side, the utterance of the speaker is mostly input simultaneously while background noise is input. Further, through the microphone 20 of the back side, the utterance signal of a speaker is input relatively slightly because the signal is attenuated as a function of a distance and noise similar to the noise through a microphone 10 of the front side is input. Thus, a speaker direction signal is actually input via the front side microphone 10, like reference number 30 of FIG. 2 and a noise direction signal having a relatively small size of a voice signal is input via the back side microphone 20, like reference number 40.
An internal block diagram of an apparatus functioning to separate a noise signal from a voice signal by mounting such two microphones is shown in FIG. 3. Referring to FIG. 3, when a signal in a speaker direction microphone 310 and a signal in a noise direction microphone 320 are input, the time-domain signal is converted to a frequency-domain signal through each frequency domain conversion unit 330A, 330B. The converted frequency domain signal is divided into a noise signal and a voice signal via a signal separation algorithm 340. Herein, a usable algorithm includes a signal separation algorithm such as a blind signal separation, a beam-forming algorithm, etc., which acts to separate a voice signal and a noise signal from two incoming signals. Such a separated signal contains remaining noise, and a remaining noise eliminator 350 outputs a voice signal with the remaining noise removed. Because the signal up to this point is a frequency domain signal, a time domain conversion unit 360 re-converts the voice signal in the frequency domain into a time domain signal.
Supposing that there are N signals basically, the prior art signal separating algorithm can separate all signals only when there are inputs through N microphones. Therefore, if there are two signals including a voice signal and a noise signal, a two microphone-using noise removal method is used for signal separation. But, because a noise signal in an actual environment is not a single pure signal but is a mixed signal containing various types of noise, it is impossible to completely remove noise by using the blind signal separation algorithm, which requires a strong dependence on a post-processor. Further, in an environment where a lot of reverberations occur, the reverberations may delude a user to recognize existence of multiple signals and it is thus impossible to properly carry out the noise removal processing. In this case, only when a post-processor has good performance as well, it is possible to remove the noise and prevent a sound quality distortion. Also, in the case of using a beam-forming algorithm as a signal separation algorithm, it is possible to remove noise only when the beam is formed in a desired direction by using many microphones. Therefore, it is difficult to achieve good performance by using only two microphones.